scholarly journals A hierarchical model of daily stream temperature for regional predictions

2018 ◽  
Author(s):  
Daniel J Hocking ◽  
Kyle O'Neil ◽  
Benjamin H Letcher
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Hierarchical Model ◽  
Mean Squared Error ◽  
Thermal Sensitivity ◽  
Stream Temperature ◽  
Eastern United States ◽  
Validation Data ◽  
Temperature Records ◽  
Use Factors

Stream temperature is an important exogenous factor influencing populations of stream organisms such as fish, amphibians, and invertebrates. Many states regulate stream protections based on temperature. Therefore, stream temperature models are important, particularly for estimating thermal regimes in unsampled space and time. To help meet this need, we developed a hierarchical model of daily stream temperature and applied it across the eastern United States. Our model accommodates many of the key challenges associated with daily stream temperature models including the lagged response of water temperature to changes in air temperature, incomplete and widely-varying observed time series, spatial and temporal autocorrelation, and the inclusion of predictors other than air temperature. We used 248,517 daily stream temperature records from 1,352 streams to fit our model and 100,909 records were withheld for model validation. Our model had a root mean squared error of 0.61 C for the fitted data and 2.03 C for the validation data, indicating excellent fit and good predictive power for understanding regional temperature patterns. We then used our model to predict daily stream temperatures from 1980 - 2015 for all streams <200 km2 from Maine to Virginia. From these, we calculated derived stream metrics including mean July temperature, mean summer temperature, and the thermal sensitivity of each stream reach to changes in air temperature. Although generally water temperature follows similar latitudinal and altitudinal patterns as air temperature, there are considerable differences at the reach scale based on landscape and land-use factors.

scholarly journals A hierarchical model of daily stream temperature for regional predictions

2018 ◽  
Author(s):  
Daniel J Hocking ◽  
Kyle O'Neil ◽  
Benjamin H Letcher
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Hierarchical Model ◽  
Mean Squared Error ◽  
Thermal Sensitivity ◽  
Stream Temperature ◽  
Eastern United States ◽  
Validation Data ◽  
Temperature Records ◽  
Use Factors

Stream temperature is an important exogenous factor influencing populations of stream organisms such as fish, amphibians, and invertebrates. Many states regulate stream protections based on temperature. Therefore, stream temperature models are important, particularly for estimating thermal regimes in unsampled space and time. To help meet this need, we developed a hierarchical model of daily stream temperature and applied it across the eastern United States. Our model accommodates many of the key challenges associated with daily stream temperature models including the lagged response of water temperature to changes in air temperature, incomplete and widely-varying observed time series, spatial and temporal autocorrelation, and the inclusion of predictors other than air temperature. We used 248,517 daily stream temperature records from 1,352 streams to fit our model and 100,909 records were withheld for model validation. Our model had a root mean squared error of 0.61 C for the fitted data and 2.03 C for the validation data, indicating excellent fit and good predictive power for understanding regional temperature patterns. We then used our model to predict daily stream temperatures from 1980 - 2015 for all streams <200 km2 from Maine to Virginia. From these, we calculated derived stream metrics including mean July temperature, mean summer temperature, and the thermal sensitivity of each stream reach to changes in air temperature. Although generally water temperature follows similar latitudinal and altitudinal patterns as air temperature, there are considerable differences at the reach scale based on landscape and land-use factors.

Evaluating and modelling the impacts of climate change and reference datasets on river water temperatures for a hydropower system with two outlets

2020 ◽  
Author(s):  
Philippe Gatien
Keyword(s):  
Climate Change ◽  
Water Temperature ◽  
Air Temperature ◽  
River Flow ◽  
Mean Squared Error ◽  
Meteorological Data ◽  
Delta Method ◽  
Weather Data ◽  
Monthly Basis ◽  
Reanalysis Dataset

&lt;p&gt;Water temperature modelling has become an essential tool in the management of ectotherm species downstream of dams in North American rivers. The main objective of this project is to compare different datasets and their ability to adequately simulate water temperatures in the Nechako River, (B.C., Canada) downstream of a major dam where the flow is not managed for hydroelectric production, but spills are programmed to cool the downstream reaches. This will ultimately lead to a reassessment of water management in the context of climate change to ensure the survival of fish migrating or living in the reaches located downstream of the dam during warm periods.&lt;/p&gt;&lt;p&gt;Water in the Nechako River stems from the Nechako reservoir at the Skins lake spillway and flows into river through a series of lakes prior to reaching Finmoore, where federal regulations stipulate that water temperatures must be maintained below 20 &amp;#176;C. The river has multiple tributaries on it&amp;#8217;s 250 km journey including the Nautley river. The river flow is simulated using a 1D unsteady flow simulation and lateral inflows using HEC-RAS.&lt;/p&gt;&lt;p&gt;Water temperature simulations are then conducted using different datasets. The first is a series of observed meteorological data spanning from 2017 to present day from two different weather stations near the river. The second dataset is ERA5, a reanalysis product that&amp;#8217;s gridded every 0.25&amp;#176;. Eleven stations nearest to the river were extracted over the same period as the observations. Both datasets were used to calibrate five parameters (dust coefficient, three wind function parameters and the Richardson number) three times using the mean absolute error (MAE), Nash-Sutcliffe coefficient (NS) and root mean squared error (RMSE) by comparing the observed and simulated temperatures near Finmoore.&lt;/p&gt;&lt;p&gt;Individual calibrations were performed over each available summer from early June to late August and then validated over the rest of the data to ensure the robustness of the results.&lt;/p&gt;&lt;p&gt;Overall, the reanalysis dataset outperformed the available observations for thermal representation of the river.&lt;/p&gt;&lt;p&gt;To further understand the thermal model, a sensitivity analysis was performed on the different inputs (inflow water temperature, air temperature, wind speed, etc.). The model showed very little sensitivity to the characteristics of the inflow (temperature, volume) as the point of interest was so far downstream. In fact, environmental factors such as air temperature had a greater impact on water temperature than upstream conditions at the reservoir spillway. This effect seems to be mostly attributable to Cheslatta Lake with its long water residence time that can reach upwards of three days.&lt;/p&gt;&lt;p&gt;The potential effects of climate change on water temperature were then investigated by modifying existing weather data like air temperature with the delta method on a monthly basis using the RCP8.5 emission scenario. Water temperatures increased throughout by roughly 2.5&amp;#176;C downstream, near Finmoore.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Climate and basin drivers of seasonal river water temperature dynamics

2017 ◽  
Vol 21 (6) ◽  
pp. 3231-3247 ◽  
Author(s):  
Cédric L. R. Laizé ◽  
Cristian Bruna Meredith ◽  
Michael J. Dunbar ◽  
David M. Hannah
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Temporal Variability ◽  
Stream Water ◽  
Stream Temperature ◽  
Short Wave ◽  
Specific Humidity ◽  
Wave Radiation ◽  
Spatial And Temporal Variability ◽  
Wide Range

Abstract. Stream water temperature is a key control of many river processes (e.g. ecology, biogeochemistry, hydraulics) and services (e.g. power plant cooling, recreational use). Consequently, the effect of climate change and variability on stream temperature is a major scientific and practical concern. This paper aims (1) to improve the understanding of large-scale spatial and temporal variability in climate–water temperature associations, and (2) to assess explicitly the influence of basin properties as modifiers of these relationships. A dataset was assembled including six distinct modelled climatic variables (air temperature, downward short-wave and long-wave radiation, wind speed, specific humidity, and precipitation) and observed stream temperatures for the period 1984–2007 at 35 sites located on 21 rivers within 16 basins (Great Britain geographical extent); the study focuses on broad spatio-temporal patterns, and hence was based on 3-month-averaged data (i.e. seasonal). A wide range of basin properties was derived. Five models were fitted (all seasons, winter, spring, summer, and autumn). Both site and national spatial scales were investigated at once by using multi-level modelling with linear multiple regressions. Model selection used multi-model inference, which provides more robust models, based on sets of good models, rather than a single best model. Broad climate–water temperature associations common to all sites were obtained from the analysis of the fixed coefficients, while site-specific responses, i.e. random coefficients, were assessed against basin properties with analysis of variance (ANOVA). All six climate predictors investigated play a role as a control of water temperature. Air temperature and short-wave radiation are important for all models/seasons, while the other predictors are important for some models/seasons only. The form and strength of the climate–stream temperature association vary depending on season and on water temperature. The dominating climate drivers and physical processes may change across seasons and across the stream temperature range. The role of basin permeability, size, and elevation as modifiers of the climate–water temperature associations was confirmed; permeability has the primary influence, followed by size and elevation. Smaller, upland, and/or impermeable basins are the most influenced by atmospheric heat exchanges, while larger, lowland and permeable basins are the least influenced. The study showed the importance of accounting properly for the spatial and temporal variability of climate–stream temperature associations and their modification by basin properties.

scholarly journals Climate change and stream temperature projections in the Columbia River basin: habitat implications of spatial variation in hydrologic drivers

2014 ◽  
Vol 18 (12) ◽  
pp. 4897-4912 ◽  
Author(s):  
D. L. Ficklin ◽  
B. L. Barnhart ◽  
J. H. Knouft ◽  
I. T. Stewart ◽  
E. P. Maurer ◽  
...  
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
General Circulation ◽  
Thermal Sensitivity ◽  
Circulation Model ◽  
Columbia River ◽  
Stream Temperature ◽  
Hydrologic Model ◽  
Columbia River Basin ◽  
Ecological Province

Abstract. Water temperature is a primary physical factor regulating the persistence and distribution of aquatic taxa. Considering projected increases in air temperature and changes in precipitation in the coming century, accurate assessment of suitable thermal habitats in freshwater systems is critical for predicting aquatic species' responses to changes in climate and for guiding adaptation strategies. We use a hydrologic model coupled with a stream temperature model and downscaled general circulation model outputs to explore the spatially and temporally varying changes in stream temperature for the late 21st century at the subbasin and ecological province scale for the Columbia River basin (CRB). On average, stream temperatures are projected to increase 3.5 °C for the spring, 5.2 °C for the summer, 2.7 °C for the fall, and 1.6 °C for the winter. While results indicate changes in stream temperature are correlated with changes in air temperature, our results also capture the important, and often ignored, influence of hydrological processes on changes in stream temperature. Decreases in future snowcover will result in increased thermal sensitivity within regions that were previously buffered by the cooling effect of flow originating as snowmelt. Other hydrological components, such as precipitation, surface runoff, lateral soil water flow, and groundwater inflow, are negatively correlated to increases in stream temperature depending on the ecological province and season. At the ecological province scale, the largest increase in annual stream temperature was within the Mountain Snake ecological province, which is characterized by migratory coldwater fish species. Stream temperature changes varied seasonally with the largest projected stream temperature increases occurring during the spring and summer for all ecological provinces. Our results indicate that stream temperatures are driven by local processes and ultimately require a physically explicit modeling approach to accurately characterize the habitat regulating the distribution and diversity of aquatic taxa.

Landscape Influences on Stream Habitats and Biological Assemblages

2006 ◽  
Keyword(s):  
Spatial Variation ◽  
Water Temperature ◽  
Air Temperature ◽  
Forest Cover ◽  
Global Climate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Covariance Structure ◽  
Stream Temperature ◽  
Landscape Features

<em>Abstract.</em>—Relatively little information is available regarding the environmental factors influencing water temperature in streams draining low-elevation, glaciated landscapes in the upper Midwest. We used multiple regression analysis and covariance structure analysis (CSA) to identify the landscape features that influence spatial variation in mean July water temperature in 282 lower Michigan stream sites and to determine the spatial scales over which these features operate. Both modeling approaches explained from 63% to 65% of the spatial variation in stream temperatures and suggested that thermal regimes in lower Michigan are influenced by a suite of landscape factors operating at catchment and local scales. However, CSA, because it incorporated both direct and indirect effects, provided a more robust approach for identifying the relative influence of landscape features on stream temperature. Our CSA model suggested that catchment area, latitude, local groundwater inputs, local forest cover, air temperature, percent catchment agriculture, percent catchment lakes and wetlands, and percent catchment coarse-textured geology were important factors structuring spatial variation in stream temperatures. Our analysis also suggested that impacts on stream temperature from land cover/ land use changes are of similar or greater magnitude as those resulting from increases in air temperature associated with global climate warming.

scholarly journals Climate and basin drivers of seasonal river water temperature dynamics

2016 ◽  
Author(s):  
C. L. R. Laizé ◽  
C. Bruna Meredith ◽  
M. Dunbar ◽  
D. M. Hannah
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Temporal Variability ◽  
Stream Water ◽  
Spatial Scales ◽  
Stream Temperature ◽  
Random Coefficients ◽  
Specific Humidity ◽  
Spatial And Temporal Variability ◽  
Wide Range

Abstract. Stream water temperature is a key control of many river processes (e.g. ecology, biogeochemistry, hydraulics) and services (e.g. power plant cooling, recreational use). Consequently, the effect of climate change and variability on stream temperature is a major scientific and practical concern. This paper aimed (1) to improve the understanding of large-scale spatial and temporal variability in climate–water temperature associations, and (2) to assess explicitly the influence of basin properties as modifiers of these relationships. A dataset was assembled including six distinct modelled climatic variables (air temperature, downward shortwave and longwave radiation, wind speed, specific humidity, and precipitation) and observed stream temperatures for the period 1984–2007 at 35 sites located on 21 rivers within 16 basins (Great Britain geographical extent); the study focused on broad spatio-temporal patterns hence was based on three-month averaged data (i.e. seasonal). A wide range of basin properties was derived. Five models were fitted (all seasons, winter, spring, summer, and autumn). Both site and national spatial scales were investigated at once by using multi-level modelling with linear multiple regressions. Model selection used Multi-Model Inference, which provides more robust models, based on sets of good models, rather than a single best model. Broad climate-water temperature associations common to all sites were obtained from the analysis of the fixed coefficients, while site-specific responses, i.e. random coefficients, were assessed against basin properties with ANOVA. All six climate predictors investigated play a role as a control of water temperature. Air temperature and shortwave radiation are important for all models/seasons, while the other predictors are important for some models/seasons only. The form and strength of the climate-stream temperature association vary depending on season and on water temperature. The dominating climate drivers and physical processes may change across seasons, and across the stream temperature range. The role of basin permeability, size, and elevation as modifiers of the climate-water temperature associations was confirmed; permeability has the primary influence, followed by size and elevation. Smaller, upland, and/or impermeable basins are the most influenced by atmospheric heat exchanges, while larger, lowland and permeable basins are least influenced. The study showed the importance of accounting properly for the spatial and temporal variability of climate-stream temperature associations and their modification by basin properties.

scholarly journals Stream temperature evolution in Switzerland over the last 50 years

2019 ◽  
Author(s):  
Adrien Michel ◽  
Tristan Brauchli ◽  
Michael Lehning ◽  
Bettina Schaefli ◽  
Hendrik Huwald
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Temporal Trends ◽  
Stream Temperature ◽  
Strengthening Effect ◽  
Temperature Trends ◽  
Glacier Melt ◽  
Hydrological Variable ◽  
Wide Range ◽  
Alpine Rivers

Abstract. Stream temperature is a key hydrological variable for ecosystem and water resources management and is particularly sensitive to climate warming. Despite the wealth of meteorological and hydrological data, few studies have quantified observed stream temperature trends in the Alps. This study presents a detailed analysis of stream temperatures in 52 catchments in Switzerland, a country covering a wide range of alpine and lowland hydrological regimes. The influence of discharge, precipitation, air temperature and upstream lakes on stream temperatures and their temporal trends is analysed from multi-decade to seasonal time scales. Stream temperature has significantly increased over the past 5 decades, with positive trends for all four seasons. The mean trends for the last 20 years are +0.37 °C per decade for water temperature, resulting from joint effects of trends in air temperature (+0.39 °C per decade) in discharge (−10.1 % per decade) and in precipitation (−9.3 % per decade). For a longer time period (1979–2018), the trends are +0.33 °C per decade for water temperature, +0.46 °C per decade for air temperature, −3.0 % per decade for discharge and −1.3 % per decade for precipitation. We furthermore show that in alpine streams, snow and glacier melt compensates air temperature warming trends in a transient way. Lakes, on the contrary have a strengthening effect on downstream water temperature trends at all elevations. The identified stream temperature trends are furthermore shown to have critical impacts on ecological temperature thresholds, especially in lowland rivers, suggesting that these are becoming more vulnerable to the increasing air temperature forcing. Resilient alpine rivers are expected to become more vulnerable to warming in the near future due to the expected reductions in snow- and glacier melt inputs.

scholarly journals Stream temperature and discharge evolution in Switzerland over the last 50 years: annual and seasonal behaviour

2020 ◽  
Vol 24 (1) ◽  
pp. 115-142 ◽  
Author(s):  
Adrien Michel ◽  
Tristan Brauchli ◽  
Michael Lehning ◽  
Bettina Schaefli ◽  
Hendrik Huwald
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Water Resource Management ◽  
Temporal Trends ◽  
Stream Temperature ◽  
Mathematical Framework ◽  
Strengthening Effect ◽  
Temperature Trends ◽  
Glacier Melt ◽  
Wide Range

Abstract. Stream temperature and discharge are key hydrological variables for ecosystem and water resource management and are particularly sensitive to climate warming. Despite the wealth of meteorological and hydrological data, few studies have quantified observed stream temperature trends in the Alps. This study presents a detailed analysis of stream temperature and discharge in 52 catchments in Switzerland, a country covering a wide range of alpine and lowland hydrological regimes. The influence of discharge, precipitation, air temperature, and upstream lakes on stream temperatures and their temporal trends is analysed from multi-decadal to seasonal timescales. Stream temperature has significantly increased over the past 5 decades, with positive trends for all four seasons. The mean trends for the last 20 years are +0.37±0.11 ∘C per decade for water temperature, resulting from the joint effects of trends in air temperature (+0.39±0.14 ∘C per decade), discharge (-10.1±4.6 % per decade), and precipitation (-9.3±3.4 % per decade). For a longer time period (1979–2018), the trends are +0.33±0.03 ∘C per decade for water temperature, +0.46±0.03°C per decade for air temperature, -3.0±0.5 % per decade for discharge, and -1.3±0.5 % per decade for precipitation. Furthermore, we show that snow and glacier melt compensates for air temperature warming trends in a transient way in alpine streams. Lakes, on the contrary, have a strengthening effect on downstream water temperature trends at all elevations. Moreover, the identified stream temperature trends are shown to have critical impacts on ecological and economical temperature thresholds (the spread of fish diseases and the usage of water for industrial cooling), especially in lowland rivers, suggesting that these waterways are becoming more vulnerable to the increasing air temperature forcing. Resilient alpine rivers are expected to become more vulnerable to warming in the near future due to the expected reductions in snow- and glacier-melt inputs. A detailed mathematical framework along with the necessary source code are provided with this paper.

Sign in / Sign up

Export Citation Format

Share Document